ENBIS-18 in Nancy

2 – 25 September 2018; Ecoles des Mines, Nancy (France) Abstract submission: 20 December 2017 – 4 June 2018

Run-to-Run Control Based on Gaussian Bayesian Network in Semiconductor Manufacturing

3 September 2018, 14:00 – 14:20

Abstract

Submitted by
Wei-Ting Yang
Authors
Wei-Ting Yang (École des Mines de Saint-Étienne), Jakey Blue (École des Mines de Saint-Étienne), Agnès Roussy (École des Mines de Saint-Étienne), Marco S. Reis (University of Coimbra), Jacques Pinaton (STMicroelectronics)
Abstract
Run-to-Run (R2R) control is the process regulating scheme commonly implemented in the semiconductor industry. Typically, key process parameters are regulated with respect to the measured quality features, e.g., the wafer thickness measurements. However, wafer quality can be affected by complex factors related to the equipment condition. In this study, the equipment condition is explicitly modeled based on the sensor signals and then integrated into the core of an R2R controller. The new R2R control scheme can reduce the process variability in a more effective way.

For this aim, Gaussian Bayesian Network (GBN) is employed to analyze the implicit relationship not only between the control factors and process parameters but also among the process parameters and metrology. The cause-effect relationship between all the variables can be explicitly expressed in the form of a connected graph after applying GBN. Consequently, the variation of process parameters caused by the control factors can be estimated and the corresponding predicted metrology can be obtained simultaneously. In this regard, we are able to consider process control in a more global view.

The effectiveness of this approach is demonstrated and validated via a practical case study, in collaboration with our industrial partner.

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